C-arm based tomographic 3D imaging is applied in an increasing number of minimal invasive procedures. Due to the limited acquisition speed for a complete projection data set required for tomographic reconstruction, breathing motion is a potential source of artifacts. Intra-scan motion estimation and compensation is required. Here, a scheme for projection based local breathing motion estimation is combined with an anatomy adapted interpolation strategy and subsequent motion compensated filtered back projection. This approach is applied in animal experiments on a flat panel C-arm system delivering improved image quality in 3D liver tumor imaging.

Lu3Al5O12 (LuAG) doped with Ce3+ is a promising scintillator material with a high density and a fast response time. The light output under x-ray or y-ray excitation is however well below the theoretical limit. In this paper the influence of co-doping with Tb3+ is investigated with the aim to increase the light output. For singly doped LuAG (with Ce3+ or Tb3+) high resolution spectra are reported giving insight in the energy level structure of the two ions in LuAG. For Ce3+ zero-phonon lines and vibronic structure is observed for thetwo lowest energy d-bands and the Stokes shift (2350 cm-1) and Huang-Rhys coupling parameter (S = 9) have been determined. For Tb3+ transition to the high spin (HS) and low spin (LS) states are observed (including a zero-phonon line and vibrational structure for the highspin state). The HS-LS splitting is 5400 cm-1 which is smaller thanusually observed and is explained by a reduction of the d-f exchangecoupling parameter J by covalency. Upon replacing the smaller Lu3+ion with the larger Tb3+ ion, the crystal field splitting for the lowest d-states increases and the Ce3+ emission shows a redshift, causing the lowest d-state to shift below the 5D4 state of Tb3+ and allowing for efficient energy transfer from Tb3+ to Ce3+ down to the lowest temperatures. Luminescence decay measurements confirm efficientenergy transfer from Tb3+ to Ce3+ and provide a qualitative understanding of the energy transfer process. Co-doping with Tb3+ does not result in the desired increase in light output and an explanation based on electron trapping in defects is discussed.

It is both desirable and challenging to make interventional C-arm systems fit for cardiac cone beam CT. A number of methods towards thisgoal have been proposed, some of which even attempt to generate 4Dimages of the beating heart. A promising candidate of this type, proposed earlier by this author, is based on the (provable) assumptionthat the 3D image of the patient's thorax at an arbitrary heart phase is a spatially deformed version of a 3D reference image at some reference phase. Under this assumption, the proposal goes on, it should be possible to jointly reconstruct reference image and deformationfield using a nonlinear extension of the Algebraic Reconstruction Technique. Meanwhile, the proposed reconstruction algorithm has beenimplemented and tested with simulated and clinical data. The resultsare favorable: Reconstructed 4D images show the heart beating. In the simulated case, where the true 4D image is known, the reconstructed motion compares well with the true motion.

The paper presents the synthetic procedure and the structural characterisation of Pr3+-doped
eulytite double phosphates Sr3La(PO4)3 and Ba3Lu(PO4)3. The luminescence properties of these
materials were studied employing time-resolved VUV spectroscopy upon excitation with
synchrotron radiation. The 5d-4f emission of Pr3+ ions was detected and assigned. It was shown that
energy transfer from host to Pr3+ 5d states is quite inefficient. At the same time the materials
demonstrate unwanted defect-related emission that presents main path for relaxation of host
relaxation excitations.

Electromagnetic (EM) tracking has been recognized as a valuable toolfor tracking the interventional devices in procedures such as lungand liver biopsy and ablation. The advantage of this technology overconventional X-ray fluoroscopy or CT-guided procedures is its real-time connection to the 3D volumetric roadmap of a patients anatomywhile the intervention is performed. EM-based guidance requires tracking of the tip of the interventional device, transforming the location of the device with pre-operative CT images, and superimposing the device in the 3D images to assist physician to complete the procedure more effectively. A key requirement of this integration of datais to find automatically the mapping between EM and CT coordinate systems. Thus, skin fiducial sensors are attached to patients before acquiring the pre-operative CTs. Then, those sensors can be recognized in both CT and EM coordinate systems to calculate the transformation matrix. In order to automate the EM-based navigation workflow andreduce procedural preparation time, an automatic fiducial detectionmethod is proposed to obtain the centroids of the sensors from thepre-operative CT. The approach has been applied to 13 rabbit datasets derived from an animal study, and numerical results show that it is a reliable and efficient method for use in EM-guided application.

Computed Tomography (CT) has been widely used for assisting lung cancer detection/diagnosis and treatment. In lung cancer diagnosis, suspect lesions or regions of interest (ROIs) are usually analyzed in screening CT scans, and CT-based image-guided minimally invasive procedures are performed for further diagnosis through bronchoscopic orpercutaneous approaches. Thus, ROI segmentation is a preliminary butvital step for abnormality detection, procedural planning, and intra-procedural guidance. In lung cancer diagnosis, such ROIs can be tumors, lymph nodes, nodules, etc. They may vary in size, shape, and other complication phenomena. Manual segmentation approaches are timeconsuming, user-biased, and cannot guarantee reproducible results.Automatic methods do not require user input, but they are usually highly application-dependent. To counterbalance among efficiency, accuracy, and robustness, considerable efforts have been contributed tosemi-automatic strategies, which enable full user control, while minimizing human interactions. Among available semi-automatic approaches, the live-wire algorithm has been recognized as a valuable tool for segmentation of a wide range of ROIs from chest CT images. In thispaper, the traditional 2D live-wire method is revisited and improved for 3D ROI segmentation. In the experiments, the proposed approachis applied to a set of anatomical ROIs from 3D chest CT images, andthe results are compared with the segmentation derived from previous evaluated live-wire-based approaches.

Recently introduced combined PET/MR scanners need to handle the specific problem that a limited MR field of view sometimes truncates armor body contours, which prevents an accurate calculation of PET attenuation correction maps. Such maps of attenuation coefficients overbody structures are required for a quantitatively correct PET imagereconstruction. This paper addresses this problem by presenting a method that segments a preliminary reconstruction type of PET images,time of flight non-attenuation corrected (ToF-NAC) images, and outlining a processing pipeline that compensates the arm or body truncation with this segmentation. The impact of this truncation compensation is demonstrated together with a comparison of two segmentation methods, simple gray value threshold segmentation and a watershed algorithm on a gradient image. Our results indicate that with truncationcompensation a clinically tolerable quantitative SUV error is robustly achievable.

The proposed method simultaneously reconstructs activity and attenuation distribution of SPECT scans without usage of additional transmission scans. Moreover, in contrast to other approaches, it effectively prevents cross-talk artefacts by using a-priori atlas data and by labelling each organ with homogeneous attenuation values. The method generates a 3D-shape model of the patient and, in order to improve overall consistency between measured and estimated SPECT sinogram, modifications to the activity- and attenuation estimation are performed iteratively. Several reconstructions of patient and simulated SPECT data were investigated and reliable convergence behaviour as well as good agreement with reference images could be observed.

Large area detector computed tomography systems with fastrotating gantries enable volumetric dynamic cardiac perfusion studies. Prospectively ECG-triggered acquisitions limit the data acquisition to a predefined cardiac phase and thereby reduce X-ray dose andlimit motion artifacts. Even in the case of highly accurate prospective triggering and stable heart rate, spatial misalignment of the cardiac volumes acquired and reconstructed per cardiac cycle may occurdue to small motion pattern variations from cycle to cycle. These misalignments reduce the accuracy of the quantitative analysis of myocardial perfusion parameters on a per voxel basis. An image based solution to this problem is elastic 3D image registration of dynamic volume sequences with variable contrast, as it is introduced in thiscontribution. After circular cone-beam CT reconstruction of cardiacvolumes covering large areas of the myocardial tissue, the completeseries is aligned with respect to a chosen reference volume. The results of the quantitative perfusion analysis are compared on pig datausing the non-registered versus the registered data set. The reduced spatial misalignment leads to an improved characterization of myocardial perfusion confirming the potential of this method. Conclusions - In conclusion, an elastic image registration-based method was proposed to improve the characterization of CT-based estimates of myocardial perfusion. The techniques performance, that was visually and quantitatively assessed on three pig data sets, confirmed its potential. The proposed method may also be applied to other perfusion studies being limited by inconsistent motion states.

CT-fluoroscopy (CTF) is an efficient imaging method for guiding percutaneous lung interventions. During CTF-guided biopsy procedure, three to ten axial sectional images are captures in a very short time period to provide nearly real-time feedback to advise adjustment of the needle as it is advanced towards the target lesion. However, thisprocedure may require frequent scans and cause unnecessary radiation exposure to physicians and technicians. Its response to respiratory movements is limited and only provides narrow local anatomical dynamics. To better utilize CTF guidance, we propose a fast CT-CTF registration algorithm with respiratory motion estimation for image-guided lung intervention using electromagnetic (EM) guidance. With the pre-procedural exhale and inhale CT scans, it would be possible to estimate a series of CT images of the same patient at different respiratory phases. Then, once CTF images are captured during the intervention, our algorithm can choose the best respiratory phase-matched 3DCT image and performs a fast deformable registration to warp the 3DCT toward CTF. The new 3D CT image can then be used by the interventional system . Compared to the traditional repetitive CTF guidance,the registered CT integrates both 3D volumetric patient data and local nearly real-time anatomy for more effective and efficient guidance. Therefore, CTF is used as a nearly real-time sensor to overcomethe discrepancies between static pre-procedural CT and the patientsanatomy, so as to provide global guidance that may be supplementedwith electromagnetic (EM) tracking and reduce the number of CTF scans. The comparative results using simulated and real data showed thatour fast CT-CTF algorithm can achieve better registration accuracythan using traditional 3D algorithms for CT-CTF registration.

The 3D fusion of tracked ultrasound with a diagnostic CT image has multiple benefits in a variety of interventional applications for oncology. Still, manual registration is a considerable drawback to theclinical workflow and hinders the widespread clinical adoption of this technique. In this paper, we propose a method to allow for an image-based automated registration, aligning multimodal images of the liver. We adopt a model-based approach that rigidly matches segmentedliver shapes from ultrasound (U/S) and diagnostic CT imaging. Towards this end, a novel method which combines a dynamic region-growingmethod with a graph-based segmentation framework is introduced to address the challenging problem of liver segmentation from U/S. The method is able to extract liver boundary from U/S images after a partial surface is generated near the principal vector from an electromagnetically tracked U/S liver sweep. The liver boundary is subsequently expanded by modeling the problem as a graph-cut minimization scheme, where cost functions used to detect optimal surface topology aredetermined from adaptive priors of neighboring surface points. Thisallows including boundaries affected by shadow areas by compensatingfor varying levels of contrast. The segmentation of the liver surface is performed in 3D space for increased accuracy and robustness. The method was evaluated in a study involving 8 patients undergoing biopsy or radiofrequency ablation of the liver, yielding promising surface segmentation results based on ground-truth comparison. The proposed extended segmentation technique improved the fiducial landmarkregistration error compared to a point-based registration (7.2mm vs. 10.2mm on average, respectively), while yielding a statistically insignificant differences in tumor target registration error (p > 0.05) compared to state-of-the-art methods.

Todays state-of the art clinical computed tomography (CT) scannersexclusively use energy-integrating, scintillation detector technology, despite the fact that a part of the information carried by the transmitted x-ray photons is lost during the detection process. Roomtemperature semiconductors, like CdTe or CZT, operated in energysensitive photon-counting mode provide information about the energy of every single x-ray detection event. This capability allows novel, promising approaches to selectively image abnormal tissue types like cancerous tissue or atherosclerotic plaque with the CT modality. In thisarticle we report on recent dual K-edge imaging results obtained inthe domain of pre-clinical, energy-sensitive photon counting CT. Inthis approach, the tuning of threshold levels in the detector electronics to the K-edge energy in the attenuation of contrast agents (CA) offers highly specific, quantitative imaging of the distributionof the CA on top of the conventional, morphological image information. The combination of the high specificity of the K-edge imaging technique together with the powerful tool of targeting specific diseases in the human body by dedicated contrast materials might enrich theCT modality with capabilities of functional imaging known from thenuclear medicine imaging modalities, e.g., positron-emission-tomography but with the additional advantage of high spatial and temporal resolution. We also discuss briefly the technological difficulties tobe overcome when translating the technique to human CT imaging andpresent the results of simulations indicating the feasibility of theKedge imaging of vulnerable plaque using targeted gold nano-particles as contrast materials. Our experiments in the pre-clinical domainshow that dual-K edge imaging of iodine and gold based CAs is feasible while our simulations for the imaging of gold CAs in the clinical case support the future possibility of translating the technique to human imaging.